Title :
Rainfall estimation using A-PHONN model
Author :
Zhang, Ming ; Scofield, Roderick A.
Author_Institution :
Christopher Newport Univ., Newport News, VA, USA
Abstract :
An adaptive multi-polynomial high order neural network (A-PHONN) model has been developed. The A-PHONN model for estimating heavy convective rainfall from satellite data has been tested as well. The A-PHONN model has 6% to 16% more accuracy than the PT-HONN (polynomial and trigonometric polynomial model) and PHONN (polynomial higher order neural network) models. Using the ANSER-plus expert system, the average rainfall estimate errors for the total precipitation event could be reduced to less than 20%
Keywords :
neural nets; rain; weather forecasting; A-PHONN model; ANSER-plus expert system; adaptive multi-polynomial high order neural network model; heavy convective rainfall; rainfall estimation; satellite data; Artificial intelligence; Artificial neural networks; Floods; Neural networks; Polynomials; Power system modeling; Satellites; Tropical cyclones; USA Councils; Weather forecasting;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.938395
